Ventricular arrhythmia detection is necessary for the management of cardiac disorders and irregularities, which may be caused by a lack of blood, oxygen, in the heart tissue and cells. Usually analysis of non-invasive surface ECG signal and invasive intra-cardiac electrograms based on waveform morphology and time domain parameters is used for ventricular abnormality detection and characterization, such as by analyzing QRS complex and T wave changes. Early arrhythmia recognition and characterization, such as of ventricular tachycardia and myocardial ischemia (MI), is desirable for rhythm management of cardiac disorders and irregularities before a rhythm progresses to a life-threatening arrhythmia, such as infarction and fibrillation. Known waveform morphology and time domain parameter analysis of depolarization and repolarization processes, such as of a P wave, QRS complex, ST segment, T wave, is used for cardiac arrhythmia monitoring and identification, e.g. of atrial fibrillation (AF), myocardial ischemia and ventricular tachycardia/fibrillation (VT/VF). Typically a 12-lead electrocardiogram (ECG) and multi-channel intra-cardiac electrogram (ICEG from invasive cardiac catheters) are used for evaluation of a cardiac rhythm and events.
Known clinical systems (such as for ST segment analysis and P wave morphology detection), which perform waveform and time domain parameter analyses, are sometimes inaccurate and time-consuming. These Known electrophysiological signal (including ECG, ICEG signal) processing systems also require extensive clinical knowledge and experience. Inaccurate and subjective evaluation and diagnosis may delay cardiac rhythm management. Further, known systems usually focus on time (amplitude, latency) or frequency (power, spectrum) domain changes and analysis, which may not efficiently and accurately capture and characterize small signal changes in a portion of a cardiac signal. Consequently, known systems may have a high failure rate of arrhythmia diagnosis and increased false alarm generation. Known methods for ventricular arrhythmia diagnosis typically focus on events and involve qualitative detection and are prone to generate false alarms due to single parameter analysis, such as analysis of a magnitude of ST segment exceeding a 0.1 mV threshold. A system according to invention principles addresses these deficiencies and related problems.